Sensors are often used to obtain data that is useful in evaluating a system or a situation. For example, it may be desirable to use sensors to monitor the movement of a retaining wall for any indication that the wall is at risk of toppling. As another example, it may be desirable to use sensors to detect the formation of ice on the surface of a road. In such situations, the sensed data can be analyzed and conclusions can be drawn from the analysis.
In certain circumstances, it is difficult to identify the data that is needed to draw conclusions about a system or situation because of other data in the signal. For example, in the case of the retaining wall monitoring, it may be difficult to identify the effect of precipitation on the retaining wall because the effects of temperature expansion are so much greater in magnitude. In the case of the ice formation detection, it may be difficult to detect precipitation on a road surface because the effects of ambient temperature change are so much greater in magnitude. In both situations, small pattern changes are difficult to identify due to the presence of substantial environmental effects, which act as noise that conceals the small pattern changes.
From the above discussion, it can be appreciated that it would be desirable to have a system or method that can be used to detect such small pattern changes in sensed data.